Comparative Multi‐Omics Survey Reveals Novel Specialized Metabolites and Biosynthetic Gene Clusters Under <scp>GacS</scp> Control in <i>Pseudomonas donghuensis</i> Strain <scp>SVBP6</scp>
Bibliographic record
Abstract
In Pseudomonas donghuensis SVBP6, isolated from an agricultural field, the well-conserved Gac-Rsm pathway upregulates biosynthesis of the antifungal compound 7-hydroxytropolone (7-HT). However, 7-HT does not fully explain the strain's Gac-Rsm-dependent antimicrobial activity. Here, we combined comparative transcriptomic, proteomic, and metabolomic approaches to identify novel GacS-dependent biosynthetic gene clusters (BGC) and/or extracellular specialized metabolites. Our data revealed a broad impact of GacS on gene expression and extracellular metabolite profile of SVBP6. At both the mRNA and polypeptide levels, specialized metabolism was the main affected functional category in the gacS mutant. The major extracellular MS/MS spectral families promoted by GacS were fatty acid amides, fatty acids, and alkaloids. GacS was required for the production of the antimicrobial compound pseudoiodinine and to activate expression of the corresponding BGC. We also detected GacS-dependent production of 2,3,4-trihydro-β-carboline-1-one, which may add to the antimicrobial arsenal of SVBP6. Furthermore, transcriptomics and proteomics pinpointed several GacS-activated BGCs that had escaped in silico genome mining tools. Altogether, comparative multi-omics analyses of gacS loss-of-function mutants in Pseudomonas isolates are a promising strategy to uncover bioactive metabolites and/or their BGCs. Discovery of novel natural products is important for harnessing the potential of microbiota to improve crop plant growth and health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".